Drones Swarm Recharging: Modeling Using Agent-Based Simulation

Leonardo Grando, E. Ursini, Paulo S. Martins
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引用次数: 0

Abstract

This work seeks to address one of the most critical problems of Flying Ad Hoc Networks (FANET), which is the issue of recharging batteries coordination. For recharges to be carried out in the best possible way, the number of load devices (Base Stations) should not be excessively high so as not to burden the network. On the other hand, it is also necessary that when the drones want to recharge, there must always be a source of energy available. For this, we propose internal estimators that provide intelligence to the drones to try to predict the next charger attendance rate. The drones will not have communication with each other to recharge coordination but will continue to communicate concerning other routine activities (note that this communication is not considered in the scope of this model), that is, for recharging the batteries' coordination, there will be no energy expenditure on communication. The verification of the suitability of the proposal is done through Agent-Based Simulation and the use of three different policies for decision making. This will enable an approach that aims to optimize the operation of the system through a Nash equilibrium.
无人机群充电:基于agent的仿真建模
这项工作旨在解决飞行自组织网络(FANET)最关键的问题之一,即电池充电协调问题。为了尽可能以最佳方式进行充值,负载设备(基站)的数量不应过高,以免给网络造成负担。另一方面,当无人机想要充电时,也必须有一个可用的能量来源。为此,我们提出了内部估计器,为无人机提供智能,以尝试预测下一个充电器的出勤率。无人机之间不会进行充电协调的通信,而是继续进行其他日常活动的通信(注意,此通信不考虑在本模型的范围内),即对于电池的充电协调,不存在通信上的能量消耗。通过基于agent的仿真和使用三种不同的决策策略来验证提案的适用性。这将使一种旨在通过纳什均衡优化系统运行的方法成为可能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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